This inventor holds 1 USPTO granted patent and 1 published patent application. Active years: 2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Years Active: 2026
Title: Roei Yehuda: Inventor in Retinal Imaging and Machine Learning.
Introduction
Roei Yehuda is an inventor associated with Jerusalem, Israel. His patent work applies machine learning to the analysis of retinal images captured using optical coherence tomography (OCT).
Latest Patents
Yehuda is associated with 1 patent, titled “Machine learning classification of retinal atrophy in OCT scans.” The invention receives OCT scans taken at two different times, along with associated retinal images, and uses image registration to match corresponding pixel-column patches between the scans. A trained machine-learning model then classifies patches from the later scan as representing retinal atrophy or not.
Career Highlights
The patent describes a method for comparing retinal scan images over time and applying machine learning to identify signs of retinal atrophy. This approach combines image registration with automated classification of OCT scan data.
Collaborations
Yehuda’s listed coworkers include Leo Joskowicz and Adi Szeskin.
Conclusion
Roei Yehuda’s patent work focuses on using registered OCT images and machine learning to classify retinal atrophy, contributing an automated approach to longitudinal retinal image analysis.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile